Sea Surface Research Articles

West African Monsoon System’s Responses to Global Ocean–Regional Atmosphere Coupling

Abstract This study explores the added value (AV) of a regional Earth system model (ESM) compared to an atmosphere-only regional climate model (RCM) in simulating West African monsoon (WAM) rainfall. The primary goals are to foster discussions on the suitability of coupled RCMs for WAM projections and deepen our understanding of ocean–atmosphere coupling’s influence on the WAM system. The study employs results from dynamical downscaling of the ERA-Interim reanalysis and Max Plank Institute ESM, low resolution (MPI-ESM-LR), by two RCMs, atmosphere only (REMO) and REMO coupled with Max Planck Institute Ocean Model (MPIOM) (ROM), at ∼25-km horizontal resolution. Results show that in regions distant from coupling domain boundaries such as West Africa (WA), constraint conditions from ERA-Interim are more beneficial than coupling effects. REMO, reliant on oceanic sea surface temperatures (SSTs) from observations and influenced by ERA-Interim, is biased under coupling conditions, although coupling offers potential advantages in representing heat and mass fluxes. Contrastingly, as intended, coupling improves SSTs and monsoon fluxes’ relationships under ESM-forced conditions. In this latter case, the coupling features a dipole-like spatial structure of AV, improving precipitation over the Guinea Coast but degrading precipitation over half of the Sahel. Our extensive examination of physical processes and mechanisms underpinning the WAM system supports the plausibility of AV. Additionally, we found that the monsoonal dynamics over the ocean respond to convective activity, with the Sahara–Sahel surface temperature gradient serving as the maintenance mechanism. While further efforts are needed to enhance the coupled RCM, we advocate for its use in the context of WAM rainfall forecasts and projections.

Diverse Responses of Strong Positive SST and Rainfall Indian Ocean Dipole Events under Greenhouse Warming

Abstract Recent research has shown that there is a projected increase in the frequency of strong positive Indian Ocean dipole (spIOD) events in terms of both sea surface temperature (SST) and precipitation. However, it is not clear whether the spIOD events defined by SST and precipitation, hereafter referred to as SST-spIOD and Pr-spIOD events, respectively, will increase at the same pace under greenhouse warming. Using climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and CMIP6 that can reasonably simulate the spIOD events, here we find that the occurrence of Pr-spIOD events increases much more than that of SST-spIOD events (+217% vs +77%) under the future high-emission scenario. The diverse response stems from a notably large increase in the spIOD events with strong rainfall but moderate SST anomalies (Pr-only spIOD), which is facilitated by a change in the local meridional Hadley circulation induced by land–sea thermal contrast in addition to the background mean-state SST warming. For the spIOD events with prominent anomalies in both rainfall and SST (concurrent spIOD), their occurrences are projected to increase, but their average SST amplitude is projected to weaken. The increased occurrence is associated with a westward-extended structural change induced by mean linear zonal advection feedbacks, while the weakened event-average SST amplitude results from a more stabilized atmosphere and coincides with the projected reduction in IOD SST skewness. Our results suggest that IOD-related mitigation strategies should consider the diverse responses of different kinds of spIOD events to greenhouse warming.

Impact of Monsoon Variability on the Northern Hemisphere Terrestrial Carbon Cycle on an Interannual Time Scale

Abstract A monsoon climate covers a large portion of the global land and exhibits notable interannual variations. However, the effect of monsoon variability on the terrestrial carbon cycle has been investigated less due to the gap between physical and biogeochemical climate research communities. Here, using the FLUXCOM dataset, we show that the Northern Hemisphere land monsoon (NHLM) regions account for 40.24% (±3.40%) [±one standard deviation (SD)] of the climatological summer mean net ecosystem production (NEP) over the NH land from 1981 to 2010 and contribute 21.35% (±7.57%) to the interannual variability (IAV) in NH NEP. Using singular value decomposition (SVD), we find that the leading modes of NEP anomalies are associated with El Niño development and decay phases. During the El Niño–developing summer, a higher sea surface temperature in the tropical central-eastern Pacific results in reduced photosynthetic productivity and weaker carbon uptake because of the reduced precipitation associated with monsoon circulation changes. Precipitation is the predominant driver of NEP anomalies relative to temperature and radiation, contributing 65.20% in the NHLM regions. During the El Niño–decaying summer, abundant rainfall along the Yangtze River valley in China results in increased photosynthetic productivity and ecosystem respiration, leading to less change in carbon uptake. In other monsoon regions, photosynthesis anomalies are driven by higher temperatures, and respiration anomalies are driven by enhanced precipitation. Both of these conditions are favorable for the release of CO2 into the atmosphere. Our study highlights the impact of monsoon variability on the carbon cycle in monsoon regions during different phases of El Niño–Southern Oscillation (ENSO) evolution.

Disagreement on the North Atlantic Cold Blob Formation Mechanisms among Climate Models

Abstract Despite global warming, the sea surface temperature (SST) in the subpolar North Atlantic has decreased since the 1900s. This local cooling, known as the North Atlantic cold blob, signifies a unique role of the subpolar North Atlantic in uptaking heat and hence impacts downstream weather and climate. However, a lack of observational records and their constraints on climate models leave the North Atlantic cold blob formation mechanism inconclusive. Using simulations from phase 6 of Coupled Model Intercomparison Project, we assess the primary processes driving the North Atlantic cold blob within individual models and whether the mechanisms are consistent across models. We show that 11 out of 32 models, which we call “Cold Blob” models, simulate the subpolar North Atlantic cooling over 1900–2014. Further analyzing the heat budget of the subpolar North Atlantic SST shows that models have distinct mechanisms of cold blob formation. While 4 of the 11 Cold Blob models indicate decreased oceanic heat transport convergence (OHTC) as the key mechanism, another four models suggest changes in radiative processes making predominant contributions. The contribution of OHTC and radiative processes is comparable in the remaining three models. Such a model disagreement on the mechanism of cold blob formation may be associated with simulated base-state Atlantic meridional overturning circulation (AMOC) strength, which explains 39% of the intermodel spread in the contribution of OHTC to the simulated cold blob. Models with a stronger base-state AMOC suggest a greater role of OHTC, whereas those with a weaker base-state AMOC indicate that radiative processes are more responsible. This model discrepancy suggests that the cold blob formation mechanism diagnosed from single model should be interpreted with caution. Significance Statement The mechanisms driving sea surface temperatures over the subpolar North Atlantic to cool since the 1900s remain uncertain due to the lack of direct observations. Here, we use a temperature change decomposition framework to dissect the historical trend of surface temperature simulated in multiple global climate models. The models diverge on whether the subpolar North Atlantic cooling is induced by reduced ocean heat transport convergence or altered radiative processes. Notably, the importance of ocean heat transport convergence is influenced by the simulated base-state strength of Atlantic meridional overturning circulation and the Irminger Sea’s mixed layer depth. This finding cautions against concluding the cooling mechanism from a single model and highlights a need for ongoing observations to constrain AMOC-related climate projection in the subpolar North Atlantic.

Variability of SST through Koopman Modes

Abstract The majority of dynamical systems arising from applications show a chaotic character. This is especially true for climate and weather applications. We present here an application of Koopman operator theory to tropical and global sea surface temperature (SST) that yields an approximation to the continuous spectrum typical of these situations. We also show that the Koopman modes yield a decomposition of the datasets that can be used to categorize the variability. Most relevant modes emerge naturally, and they can be identified easily. A difference with other analysis methods such as empirical orthogonal function (EOF) or Fourier expansion is that the Koopman modes have a dynamical interpretation, thanks to their connection to the Koopman operator, and they are not constrained in their shape by special requirements such as orthogonality (as it is the case for EOF) or pure periodicity (as in the case of Fourier expansions). The pure periodic modes emerge naturally, and they form a subspace that can be interpreted as the limiting subspace for the variability. The stationary states therefore are the scaffolding around which the dynamics takes place. The modes can also be traced to the Niño variability and in the case of the global SST to the Pacific decadal oscillation (PDO). Significance Statement We compute the Koopman modes for the tropical and global SST, demonstrating that significant dynamical modes can be identified also in complex high-dimensional datasets with continuous spectra. The Koopman modes are then used to identify the stationary subspace, namely, the limit subspace for the invariant evolution of the system.

Seasonal predictions of summer compound humid heat extremes in the southeastern United States driven by sea surface temperatures

Humid heat extreme (HHE) is a type of compound extreme weather event that poses severe risks to human health. Skillful forecasts of HHE months in advance are crucial for developing strategies to enhance community resilience to extreme events1,2. This study demonstrates that the frequency of summertime HHE in the southeastern United States (SEUS) can be skillfully predicted 0–1 months in advance using the SPEAR (Seamless system for Prediction and EArth system Research) seasonal forecast system. Sea surface temperatures (SSTs) in the tropical North Atlantic (TNA) basin are identified as the primary driver of this prediction skill. The responses of large-scale atmospheric circulation and winds to anomalous warm SSTs in the TNA favor the transport of heat and moisture from the Gulf of Mexico to the SEUS. This research underscores the role of slowly varying sea surface conditions in modifying large-scale environments, thereby contributing to the skillful prediction of HHE in the SEUS. The results of this study have potential applications in the development of early warning systems for HHE.

Phytoplankton bloom detection and trends in satellite inherent optical properties over the last two decades in a heterogeneous Patagonian coastal system

ABSTRACT To effectively address ecosystem health risks, it is crucial to use detection methods that efficiently cover vast areas with good spatial resolution. These methods should enhance understanding of how phytoplankton blooms might evolve due to climate change. Satellite Ocean Color sensors are advantageous for detecting and monitoring phytoplankton blooms over time. This study uses the Inherent Optical Properties (IOP) index, which considers light absorption by phytoplankton (Ab_phy) and by detritus plus colored dissolved organic matter (Ab_adg), to detect phytoplankton blooms in six subareas within the San Matías Gulf (SMG; Patagonia, Argentina). The findings reveal a significant increase in bloom alerts over the last 20 years in the northwestern and southwestern subareas. Temporal changes in chlorophyll a (Chla) and sea surface temperature (SST) were observed, both showing an increase over the studied period. Environmental features like the diffusive attenuation coefficient (Kd_490) and Ab_phy also showed positive trends in four of the six subareas. The positive trends in SST and Kd_490 suggest a potential reduction in the euphotic zone depth. Additionally, the presence of phytoplankton biomass, indicated by Chla and Ab_phy, is linked to reduced light penetration in the water column due to absorption by the cells and self-shading. A decrease in Ab_adg was observed, while photosynthetically active radiation (PAR) showed no significant trend over the last two decades. These patterns could significantly impact the frequency and timing of phytoplankton blooms, altering their community composition and phenology. Such changes have profound implications for the entire marine food web and the ecosystem services within the SMG. The results underscore the importance of incorporating optical data for monitoring phytoplankton blooms across multiple areas.

Highest ocean heat in four centuries places Great Barrier Reef in danger

Mass coral bleaching on the Great Barrier Reef (GBR) in Australia between 2016 and 2024 was driven by high sea surface temperatures (SST)1. The likelihood of temperature-induced bleaching is a key determinant for the future threat status of the GBR2, but the long-term context of recent temperatures in the region is unclear. Here we show that the January–March Coral Sea heat extremes in 2024, 2017 and 2020 (in order of descending mean SST anomalies) were the warmest in 400 years, exceeding the 95th-percentile uncertainty limit of our reconstructed pre-1900 maximum. The 2016, 2004 and 2022 events were the next warmest, exceeding the 90th-percentile limit. Climate model analysis confirms that human influence on the climate system is responsible for the rapid warming in recent decades. This attribution, together with the recent ocean temperature extremes, post-1900 warming trend and observed mass coral bleaching, shows that the existential threat to the GBR ecosystem from anthropogenic climate change is now realized. Without urgent intervention, the iconic GBR is at risk of experiencing temperatures conducive to near-annual coral bleaching3, with negative consequences for biodiversity and ecosystems services. A continuation on the current trajectory would further threaten the ecological function4 and outstanding universal value5 of one of Earth’s greatest natural wonders.

Retrieval of spectral slope of chromophoric dissolved organic matter (S275–295) in Laptev Sea

Study regionLaptev Sea Study focusThe absorption slopes of colored dissolved organic matter (CDOM) in the spectral range of 275–295 nm (S275–295) is a reliable parameter of the source and transformation of CDOM and dissolved organic carbon (DOC) in the estuarine environment. Studying S275–295 in coastal areas can provide important information about CDOM and DOC. This study proposed a new multilayer backpropagation neural network (MBPNN) based on the relationship between S275–295 and aCDOM(443) (absorption of CDOM at 443 nm) as a customization function to invert S275–295. The model accurately estimated S275–295 with a MAPE and RMSE of 6.12 % and 0.0012 nm−1, respectively, and revealed the spatiotemporal distribution of S275–295 in the Laptev Sea between 2002 and 2022 (July to September). The effects of influencing factors on temporal and spatial variations of S275–295 were analyzed. New hydrological insights for the regionThe MBPNN model with a customization function has good performance to invert S275–295 in Laptev Sea. The S275–295 in the Laptev Sea ranged from 0.014 to 0.022 nm−1. S275–295 increased gradually from coastal waters to the open sea. Inter-annual S275–295 fluctuated, but no significant trend was observed during the study period (2002–2022). S275–295 was negatively correlated with river discharge (r=-0.41), permafrost thaw depth (r=-0.42), ice extent (r=-0.55) and Normalized Difference Vegetation Index (r=-0.46) but positively correlated with salinity (r=0.86) and wind speed (r=0.46).

Interfacial Enrichment of Lauric Acid Assisted by Long-Chain Fatty Acids, Acidity and Salinity at Sea Spray Aerosol Surfaces.

Surfactant monolayers at sea spray aerosol (SSA) surfaces regulate various atmospheric processes including gas transfer, cloud interactions, and radiative properties. Most experimental studies of SSA employ a simplified surfactant mixture of long-chain fatty acids (LCFAs) as a proxy for the sea surface microlayer or SSA surface. However, medium-chain fatty acids (MCFAs) make up nearly 30% of the FA fraction in nascent SSA. Given that LCFA monolayers are easily disrupted upon the introduction of chemical heterogeneity (such as mixed chain lengths), simple FA proxies are unlikely to represent realistic SSA interfaces. Integrating experimental and computational techniques, we characterize the impact that partially soluble MCFAs have on the properties of atmospherically relevant LCFA mixtures. We explore the extent to which the MCFA lauric acid (LA) is surface stabilized by varying acidity, salinity, and monolayer composition. We also discuss the impacts of pH on LCFA-assisted LA retention, where the presence of LCFAs may shift the surface-adsorption equilibria of laurate─the conjugate base─toward higher surface activities. Molecular dynamic simulations suggest a mechanism for the enhanced surface retention of laurate. We conclude that increased FA heterogeneity at SSA surfaces promotes surface activity of soluble FA species, altering monolayer phase behavior and impacting climate-relevant atmospheric processes.

Understanding Balanophyllia regia Distribution in the Canary Islands: Effects of Environmental Factors and Methodologies for Future Monitoring

The future of marine ecosystems is at risk due to climate change and other human impacts. Specifically, due to ocean warming, some tropical species are expanding their populations while populations of temperate species are in regression, making the establishment of conservation measures imperative to maintain local biodiversity. In this study we establish a baseline on the distribution and abundance of the temperate coral Balanophyllia regia from the Canary Islands. We found that the main environmental factors determining B. regia’s distribution and abundance were sea surface temperature and hydrodynamic conditions. Areas under large wave action and colder environments enhanced this warm-temperate species’ development. Since its metabolic performance depends exclusively on the surrounding environment, we also propose a methodology to potentially monitor climate change on coastal habitats through this azooxanthellate calcified coral. Results of a tagging experiment showed that a concentration of 20 mg/mL of calcein during 6 h might be enough to in situ label polyps of B. regia without compromising corallite survival. Long-term monitoring of population abundances and growth rates of B. regia through calcein tagging will allow us to identify alterations in local ecosystems early and focus future conservation investments on the most vulnerable areas with higher ecological and economic value.

Predicting significant wave height in the South China Sea using the SAC-ConvLSTM model

IntroductionThe precise forecasting of Significant wave height(SWH) is vital to ensure the safety and efficiency of aquatic activities such as ocean engineering, shipping, and fishing.MethodsThis paper proposes a deep learning model named SAC-ConvLSTM to perform 24-hour prediction with the SWH in the South China Sea. The long-term prediction capability of the model is enhanced by using the attention mechanism and context vectors. The prediction ability of the model is evaluated by mean absolute error (MAE), root mean square error (RMSE), mean square error (MSE), and Pearson correlation coefficient (PCC).ResultsThe experimental results show that the optimal input sequence length for the model is 12. Starting from 12 hours, the SAC-ConvLSTM model consistently outperforms other models in predictive performance. For the 24-hour prediction, this model achieves RMSE, MAE, and PCC values of 0.2117 m, 0.1083 m, and 0.9630, respectively. In addition, the introduction of wind can improve the accuracy of wave prediction. The SAC-ConvLSTM model also has good prediction performance compared to the ConvLSTM model during extreme weather, especially in coastal areas.DiscussionThis paper presents a 24-hour prediction of SWH in the South China Sea. Through comparative validation, the SAC-ConvLSTM model outperforms other models. The inclusion of wind data enhances the model's predictive capability. This model also performs well under extreme weather conditions. In physical oceanography, variables related to SWH include not only wind but also other factors such as mean wave period and sea surface air pressure. In the future, additional variables can be incorporated to further improve the model's predictive performance.

The East China Sea Kuroshio Current Intensifies Deep Convective Precipitation: A Case Study

AbstractDeep atmospheric convection is often observed over the Kuroshio in the East China Sea (ECSK). However, the mechanisms by which warm oceanic currents fuel transient deep convection are not fully understood. This study investigates an atmospheric cold front that brought heavy precipitation as it traversed the ECSK in April 2004. The southwesterlies ahead of the cold front advected moist and warm air, creating a zone with high convective available potential energy (CAPE) values. As the cold front approached the ECSK, the pre‐frontal high CAPE values coalesced with those over the warm current that substantially strengthened the deep convection, with precipitation rate increasing from 3 mm hr−1 to 10 mm hr−1. A numerical model well simulated the marked increase in precipitation over the ECSK, permitting the isolation of the ECSK's influence by contrasting the control (CTRL) run with an experiment with smoothed sea surface temperatures (SMTH run). Results show the ECSK contributed to 46% of the precipitation over the warm current. The ECSK was found to amplify ascending motion and elevate neutral buoyancy levels, extending its effect up to the tropopause. Furthermore, the strengthened deep convection significantly lowered the sea level pressure (SLP) over the ECSK and impressed upon the time‐mean SLP field. An additional experiment with lowered SST underscored the high SST's critical role in deep convection. This case study suggests a novel pathway by which the effects of warm oceanic currents influence the upper troposphere under extreme conditions with strong baroclinic instability.

Investigating fish reproduction phenology and essential habitats by identifying the main spatio-temporal patterns of fish distribution

Abstract Fish spawning phenology is a major concern for conservation and fisheries management. New intensive data sources, such as GPS-based tracking data and high-resolution catch declaration data, are becoming increasingly available in the field of marine ecology. These data benefit from high spatiotemporal resolution and open new research avenues for investigating the interannual variability in fish phenology. In this paper, we demonstrate how an integrated species distribution model informed by commercial catch data combined with spatiotemporal dimension reduction methods known as empirical orthogonal functions (EOFs) can be used to synthesize spatiotemporal signals in fish reproduction phenology. Specifically, we address the following questions: (1) Can we identify seasonal spatial patterns that can be interpreted in terms of reproductive phenology and essential habitats? (2) Can we identify changes in reproductive phenology over time? (3) Are these changes related to environmental drivers? The analysis illustrates the reproductive phenology of three key commercial species in the Bay of Biscay (sole, hake, and sea bass). The EOF analysis emphasized strong seasonal spatiotemporal patterns that correspond to reproduction patterns and feeding patterns. Based on this methodology, we identified seasonal variations in the timing of reproduction, and we related these variations to sea surface temperature, a key driver of fish reproduction.

Unveiling the Dominant Factors Controlling the Long‐Term Changes in Northwest Pacific Tropical Cyclone Intensification Rates

AbstractTropical cyclones (TCs), especially intense TCs, pose serious threats to life and property particularly in the affected coastal regions. Understanding the factors determining the TC intensification rate (IR) remains a great challenge. This study identifies the dominant factors responsible for the observed significant increase in TC IR over the western North Pacific in recent decades using the energetically based dynamical system model of TC intensification. It is found that the environmental dynamical efficiency mainly contributed by vertical wind shear and upper‐level divergence is responsible for the long‐term changes in TC IR during the strong TC stage, but it played a secondary role in the long‐term changes in IR during the weak TC stage. The latter were primarily contributed by the maximum potential intensity, which is primarily determined by sea surface temperature. Results also strongly suggest that global warming is the primary driver of the long‐term changes in TC IR.

Unraveling climate trends in the mediterranean: a hybrid machine learning and statistical approach

AbstractThis study presents a comprehensive spatiotemporal analysis of sea surface temperatures (SST) and surface air temperatures (TAS) across 15 Mediterranean coastal stations, leveraging centennial-scale data to analyze regional climate dynamics. The modeling framework integrates three sequential phases: data preprocessing, statistical analysis, and advanced machine learning techniques, creating a robust analytical pipeline. The data preprocessing phase harmonizes diverse datasets, addresses missing values, and applies transformations to ensure analytical consistency. The statistical modeling employs the Pettitt test for change point detection and linear trend analysis to unveil underlying patterns. The machine learning phase utilizes K-means clustering for climate regime classification and implements tailored Convolutional Neural Networks (CNNs) for cluster-specific future climate anomaly projections. Results unveil a marked anthropogenic climate signal, with contemporary observations consistently surpassing historical baselines. Breakpoint analyses and linear trend assessments reveal heterogeneous climatic shifts, with pronounced warming in the northern Mediterranean. Notably, Nice and Ajaccio exhibit the highest SST increases (0.0119 and 0.0113 °C/decade, respectively), contrasting with more modest trends in Alexandria (0.0052 °C/decade) and Antalya (0.0047 °C/decade) in the eastern Mediterranean. The application of clustering and CNN projections provides granular insights into differential warming trajectories. By 2050, cooler northwestern Mediterranean zones are projected to experience dramatic SST anomalies of approximately 3 °C above the average, with corresponding TAS increases of 2.5 °C. In contrast, warmer eastern and southern regions display more subdued warming patterns, with projected SST and TAS increases of 1.5–2.5 °C by mid-century. This research’s importance is highlighted by its potential to inform tailored adaptation strategies and contribute to the theoretical understanding of climate dynamics, advancing climate modeling and analysis efforts.

Understanding Local Perspectives on Climate Change and Its Impacts on Small-Scale Fishing Communities in Honda Bay, Palawan, Philippines

Climate change's adverse impacts are already evident, particularly in coastal areas. However, local perception that is essential in formulating policies for mitigating its impacts remains limited. Thus, this study evaluated the level of perception of small fishing communities on climate change and its impacts on livelihood and the environment. The data were obtained using a face-to-face survey with the aid of a structured questionnaire. They were interpreted and analyzed using the Likert point scale, descriptive statistics, and chi-square. A total of 308 male fisherfolks participated in the survey. Majority belong to age 51-60 years old (38%) and 61 years old and above (32%). Most of them (65%) finished elementary and generally (94%) rely on fishing for main source of living. As for income, 47% earned an estimated monthly income of Php 2,501-5,000 and 28% got Php 5,001-7,500. Most of the respondents are full-time fishers (89%) for more than 11 years (87%), and fishing within the municipal water (92%). Majority (90%) have an idea about climate change as reflected by their very high score in Likert Perception (24.3±2.3%). The climate change impacts perceived by the respondents include: increasing sea surface temperature (87%); fish are sensitive to changing climate (87%); and fossil fuel consumption contributes to climate change (84%). They said they got the information from TV/ Radio (99%) and social media (10%). The age (p-value < 0.0032) and source of information (p-value < 0.0348) are among the variables with significant relationship to the perception of respondents on climate change impacts. In total, it appears that majority of fishers are aware of the impacts of climates. It is suggested that effective management actions, such as emergency preparedness schemes and livelihood diversification should be explored to address the specific needs of fishing communities that are vulnerable to the impacts of climate change. Furthermore, an ecosystem-based approach that focuses on socio-economic dynamics and climate-induced changes in assessments and management is essential for the sustainable use of fisheries resources amidst the changing climate.

Internal-tide vertical structure and steric sea surface height signature south of New Caledonia revealed by glider observations

Abstract. In this study, we exploit autonomous underwater glider data to infer internal-tide dynamics south of New Caledonia, an internal-tide-generation hot spot in the southwestern tropical Pacific. By fitting a sinusoidal function to vertical displacements at each depth using a least-squares method, we simultaneously estimate diurnal and semidiurnal tides. Our analysis reveals regions of enhanced tidal activity, strongly dominated by the semidiurnal tide. To validate our findings, we compare the glider observations to a regional numerical simulation that includes tidal forcing. This comparison assesses the simulation's realism in representing tidal dynamics and evaluates the glider's ability to infer internal-tide signals and their signature in sea surface height (SSH). The glider observations and a pseudo glider, simulated using hourly numerical model output with identical sampling, exhibit similar amplitude and phase characteristics along the glider track. Existing discrepancies are in large part explained by tidal incoherence induced by eddy–internal-tide interactions. We infer the semidiurnal internal-tide signature in steric SSH by the integration of vertical displacements. Within the upper 1000 m, the pseudo glider captures roughly 78 % of the steric SSH total variance explained by the full water column signal. This value increases to over 90 % when projecting the pseudo glider's vertical displacements onto climatological baroclinic modes and extrapolating to full depth. Notably, the steric SSH from glider observations aligns closely with empirical estimates derived from satellite altimetry, highlighting the internal tide's predominant coherent nature during the glider's sampling.

Holocene insolation and sea surface temperature influences on the polar front jet stream and precipitation in the midcontinental United States

Variability in the source and seasonality of precipitation in the midcontinental United States during the Holocene was investigated using isotopic and sedimentological data from Martin Lake, northeastern Indiana, USA. Between 7100 and 4000 years before present (yr BP; present = 1950 CE), high δ18Ocal and δ13Ccal values with low variability indicate that moisture was predominantly derived from subtropical, southerly sources and delivered primarily during the warm season. Mean state shifts toward lower δ18Ocal and δ13Ccal occurred at ca. 4000 and 2550 yr BP, respectively, indicating an increase in northerly-sourced cold-season precipitation during the Late Holocene (i.e., the past 4200 years) and a subsequent reduction in warm season duration after 2550 yr BP. Record low %lithics from ca. 5000 to 4000 yr BP indicates major reductions in warm-season rain storms, consistent with regional evidence of drought at this time. An increase in the amplitude of centennial-scale variability in δ18Ocal, δ13Ccal, and %lithics after 1900 yr BP indicates greater precipitation source variability during the Common Era. During this interval, precipitation fluctuated between southerly-sourced, convective rainstorms when the Northern Hemisphere (NH) was warm (e.g., during the Medieval Climate Anomaly; 700–1000 yr BP) and northerly-sourced rain and snow when the NH was cool (e.g., during the Little Ice Age; 150–550 yr BP). These trends, especially the change at ca. 4000 yr BP, are consistent with other North American paleoclimate records that collectively suggest a continental-scale shift in precipitation seasonality during the Middle to Late Holocene transition as the tropical Pacific Ocean transitioned from La Niña-like conditions to a more El Niño-like mean state. Concurrent NH cooling and persistent El Niño-like conditions during the Late Holocene would have favored a southerly polar front jet stream with enhanced ridge and trough atmospheric circulation over North America – conditions resembling the positive mode of the Pacific-North American teleconnection (PNA). This would have increased interactions between high-latitude and subtropical airmasses over the midcontinent, increasing the proportion of northerly precipitation with low δ18O delivered during the cold season (i.e., snowfall) and during extended periods with +PNA-like atmospheric circulation (e.g., the Little Ice Age).

The Depth Distribution Law of the Polarization of the Vector Acoustic Field in the Ocean Waveguide

The polarization of the acoustic field in the ocean waveguide environment is a unique property that can provide new ideas for locating and detecting the underwater target, so it is interesting to study the polarization. This paper extends the Stokes parameters to a broadband form, and uses the non-stationary phase approximation method to simplify the expressions, reducing the complexity of theoretical derivation. A physical phenomenon is observed where polarization exhibits significant variations concerning the sea surface, seafloor, source depth, and the source symmetrical depth. Simulation results demonstrate that the simplified equations using the non-stationary phase approximation are effective. Additionally, by normalizing the broadband Stokes parameters, the effects of horizontal range on the depth distribution law of polarization can be eliminated. Subsequently, using the normalized broadband Stokes parameters, the influence of environmental and source parameters on the depth distribution law of polarization is analyzed. The effectiveness of the non-stationary phase approximation and the range-independence property of the normalized broadband Stokes parameters are verified by processing RHUM-RUM experimental data. Based on the conclusions of this paper, it is expected that the polarization can be used for target depth estimation.